In recent years, the global and Indian government efforts in monitoring and collecting data related to the fisheries industry have witnessed significant advancements. Despite this wealth of data, there exists an untapped potential for leveraging artificial intelligence based technological systems to benefit Indian fishermen in coastal areas. To fill this void in the Indian technology ecosystem, the authors introduce Jal Anveshak. This is an application framework written in Dart and Flutter that uses a Llama 2 based Large Language Model fine-tuned on pre-processed and augmented government data related to fishing yield and availability. Its main purpose is to help Indian fishermen safely get the maximum yield of fish from coastal areas and to resolve their fishing related queries in multilingual and multimodal ways.

翻译：近年来，全球及印度政府在渔业相关数据的监测与收集方面取得了显著进展。尽管数据资源丰富，但利用基于人工智能的技术系统为印度沿海地区渔民谋福利的潜力尚未得到充分开发。为填补印度技术生态系统的这一空白，本文作者提出了Jal Anveshak。这是一个基于Dart和Flutter编写的应用框架，其核心采用基于Llama 2的大型语言模型，该模型经过与渔业产量及资源相关的预处理及增强政府数据的微调。该框架的主要目的是帮助印度渔民安全地从沿海区域获取最大渔获量，并通过多语言、多模态方式解决其渔业相关疑问。